Disambiguating words with self-organizing maps
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2011
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| Online Access: | http://hdl.handle.net/1721.1/66413 |
| _version_ | 1826189041555472384 |
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| author | Couturier, Martin Marcel |
| author2 | Patrick H. Winston. |
| author_facet | Patrick H. Winston. Couturier, Martin Marcel |
| author_sort | Couturier, Martin Marcel |
| collection | MIT |
| description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011. |
| first_indexed | 2024-09-23T08:08:57Z |
| format | Thesis |
| id | mit-1721.1/66413 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T08:08:57Z |
| publishDate | 2011 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/664132022-01-13T07:54:29Z Disambiguating words with self-organizing maps Couturier, Martin Marcel Patrick H. Winston. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Electrical Engineering and Computer Science. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011. Cataloged from PDF version of thesis. Includes bibliographical references (p. 77). Today, powerful programs readily parse English text; understanding, however, is another matter. In this thesis, I take a step toward understanding by introducing CLARIFY, a program that disambiguates words. CLARIFY identifies patterns in observed word contexts, and uses these patterns to select the optimal word sense for any specific situation. CLARIFY learns successful patterns by manipulating an accelerated Self-Organizing Map to save these example contexts and then references them to perform further context based disambiguation within the language. Through this process and after training on 125 examples, CLARIFY can now decipher that shrimp in the sentence "The shrimp goes to the store. " is a small-person, not relying on a literal definition of each word as a separate element but looking at the sentence as a fluid solution of many elements, thereby making the inference crustacean absurd. CLARIFY is implemented in 1500 lines of Java. by Martin Marcel Couturier. M.Eng. 2011-10-17T21:23:17Z 2011-10-17T21:23:17Z 2011 2011 Thesis http://hdl.handle.net/1721.1/66413 755091036 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 77 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Couturier, Martin Marcel Disambiguating words with self-organizing maps |
| title | Disambiguating words with self-organizing maps |
| title_full | Disambiguating words with self-organizing maps |
| title_fullStr | Disambiguating words with self-organizing maps |
| title_full_unstemmed | Disambiguating words with self-organizing maps |
| title_short | Disambiguating words with self-organizing maps |
| title_sort | disambiguating words with self organizing maps |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/66413 |
| work_keys_str_mv | AT couturiermartinmarcel disambiguatingwordswithselforganizingmaps |